A mega-analysis of expression quantitative trait loci in retinal tissue.
Autopsy
Gene Expression
/ genetics
Gene Expression Profiling
/ methods
Gene Expression Regulation
/ genetics
Genetic Predisposition to Disease
/ genetics
Genetic Variation
/ genetics
Genome-Wide Association Study
/ methods
Genomics
/ methods
Genotype
Healthy Volunteers
Humans
Phenotype
Polymorphism, Single Nucleotide
/ genetics
Quantitative Trait Loci
/ genetics
Retina
/ metabolism
Retinal Diseases
/ genetics
Journal
PLoS genetics
ISSN: 1553-7404
Titre abrégé: PLoS Genet
Pays: United States
ID NLM: 101239074
Informations de publication
Date de publication:
09 2020
09 2020
Historique:
received:
27
01
2020
accepted:
15
06
2020
entrez:
2
9
2020
pubmed:
2
9
2020
medline:
18
11
2020
Statut:
epublish
Résumé
Significant association signals from genome-wide association studies (GWAS) point to genomic regions of interest. However, for most loci the causative genetic variant remains undefined. Determining expression quantitative trait loci (eQTL) in a disease relevant tissue is an excellent approach to zoom in on disease- or trait-associated association signals and hitherto on relevant disease mechanisms. To this end, we explored regulation of gene expression in healthy retina (n = 311) and generated the largest cis-eQTL data set available to date. Genotype- and RNA-Seq data underwent rigorous quality control protocols before FastQTL was applied to assess the influence of genetic markers on local (cis) gene expression. Our analysis identified 403,151 significant eQTL variants (eVariants) that regulate 3,007 genes (eGenes) (Q-Value < 0.05). A conditional analysis revealed 744 independent secondary eQTL signals for 598 of the 3,007 eGenes. Interestingly, 99,165 (24.71%) of all unique eVariants regulate the expression of more than one eGene. Filtering the dataset for eVariants regulating three or more eGenes revealed 96 potential regulatory clusters. Of these, 31 harbour 130 genes which are partially regulated by the same genetic signal. To correlate eQTL and association signals, GWAS data from twelve complex eye diseases or traits were included and resulted in identification of 80 eGenes with potential association. Remarkably, expression of 10 genes is regulated by eVariants associated with multiple eye diseases or traits. In conclusion, we generated a unique catalogue of gene expression regulation in healthy retinal tissue and applied this resource to identify potentially pleiotropic effects in highly prevalent human eye diseases. Our study provides an excellent basis to further explore mechanisms of various retinal disease etiologies.
Identifiants
pubmed: 32870927
doi: 10.1371/journal.pgen.1008934
pii: PGENETICS-D-20-00131
pmc: PMC7462281
doi:
Types de publication
Journal Article
Research Support, N.I.H., Intramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e1008934Subventions
Organisme : Intramural NIH HHS
ID : ZIA EY000450
Pays : United States
Organisme : Intramural NIH HHS
ID : ZIA EY000546
Pays : United States
Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
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